Is Target-Based Drug Discovery Efficient? Discovery and “Off-Target” Mechanisms of All Drugs

Target-based
drug discovery is the dominant paradigm of drug discovery;
however, a comprehensive evaluation of its real-world efficiency is
lacking. Here, a manual systematic review of about 32000 articles
and patents dating back to 150 years ago demonstrates its apparent
inefficiency. Analyzing the origins of all approved drugs reveals
that, despite several decades of dominance, only 9.4% of small-molecule
drugs have been discovered through “target-based” assays.
Moreover, the therapeutic effects of even this minimal share cannot
be solely attributed and reduced to their purported targets, as they
depend on numerous off-target mechanisms unconsciously incorporated
by phenotypic observations. The data suggest that reductionist target-based
drug discovery may be a cause of the productivity crisis in drug discovery.
An evidence-based approach to enhance efficiency seems to be prioritizing,
in selecting and optimizing molecules, higher-level phenotypic observations
that are closer to the sought-after therapeutic effects using tools
like artificial intelligence and machine learning.

基于靶点的药物发现（Target-based drug discovery）是当前药物研发领域的主流范式；然而，目前仍缺乏对其真实世界应用效率的全面评估。本文对追溯至150年前的约3.2万篇文献与专利开展手动系统综述，证实了该范式的显著低效性。通过分析所有已获批药物的起源，研究发现：尽管该范式主导药物研发数十年，但仅有9.4%的小分子药物是通过“基于靶点的”筛选实验发现的。此外，即便占比极低的这部分药物，其治疗效应也无法完全归因并简化至其所宣称的靶点——因为它们的作用机制依赖于诸多在表型观察过程中无意识纳入的脱靶作用机制。研究数据表明，以还原论为导向的基于靶点的药物发现，或为药物研发领域生产力危机的诱因之一。有证据显示，提升研发效率的循证路径，应优先在分子筛选与优化环节，借助人工智能、机器学习等工具，采用更贴近预期治疗效应的高阶表型观察策略。